Pandas Split DataFrame using row index

Question

I want to split dataframe by uneven number of rows using row index.

The below code:

groups = df.groupby((np.arange(len(df.index))/l[1]).astype(int)         


        

Answer 1

You can create an array to use for indexing via NumPy:

import pandas as pd, numpy as np

df = pd.DataFrame(np.arange(24).reshape((8, 3)), columns=list('abc'))

L = [2, 5, 7]
idx = np.cumsum(np.in1d(np.arange(len(df.index)), L))

for _, chunk in df.groupby(idx):
    print(chunk, '\n')

   a  b  c
0  0  1  2
1  3  4  5 

    a   b   c
2   6   7   8
3   9  10  11
4  12  13  14 

    a   b   c
5  15  16  17
6  18  19  20 

    a   b   c
7  21  22  23 

Instead of defining a new variable for each dataframe, you can use a dictionary:

d = dict(tuple(df.groupby(idx)))

print(d[1])  # print second groupby value

    a   b   c
2   6   7   8
3   9  10  11
4  12  13  14